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Source channel @githubtrending · Post #15365 · Dec 24

#jupyter_notebook DINOv3 offers powerful self-supervised vision models from Meta AI, like ViT up to 7B parameters and ConvNeXt, pretrained on 1.7B web or satellite images. Load them easily via PyTorch Hub, Hugging Face Transformers (v4.56+), or timm (v1.0.20+), with code examples for features, depth, detection, and segmentation. You benefit by using these top-performing, dense features without fine-tuning or labels—saving time and compute for tasks like classification, object detection, and zero-shot analysis on your images. https://github.com/facebookresearch/dinov3

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Crypto M - Crypto News

@CryptoM · Post #65322 · 04/12/2026, 11:03 PM

🚀 AI TRENDS | MiniMax M2.7 Open Source Launches Globally with Key Partnerships On April 13, Jin10 reported that MiniMax, a domestic AI model company, announced the global open-source release of MiniMax M2.7 on April 12. According to Jin10, the launch involved collaborations with major chip manufacturers and inference platforms, including Huawei Ascend, Moore Threads, Muxi, Kunlunxin, NVIDIA, Together AI, Fireworks, and Ollama. On the first day of the open-source release, the model integration and inference adaptation were successfully completed. #AI#MiniMax#M2.7 #OpenSource#GlobalLaunch#Partnerships#HuaweiAscend#MooreThreads#Muxi#Kunlunxin#NVIDIA#TogetherAI#Fireworks#Ollama#InferencePlatforms#ChipManufacturers